We evaluate the quality of the clusterings using metrics such as cluster accuracy, NMI, ARI. To compute clustering accuracy, we are required to solve an assignment problem (computed using a Hungarian match[1]}, [2]}) between the true class labels and the cluster assignment. In our analysis, we observe that using K-means with the embeddings of ID block achieved better clustering accuracy and we use this method throughout the paper while evaluating our proposed algorithm.
